Welcome to Ruocheng Guo's homepage.

Ruocheng is a Ph.D. student @ Arizona State University, now he is affiliated with Data Mining and Machine Learning Lab, under supervision of Prof. Huan Liu.

Before joining ASU, Ruocheng received M.Sc degree in Electronic Engineering from the most beautiful Hong Kong University of Science and Technology in Hong Kong, China and B.Eng degree in Electrical Engineering from Huazhong University of Science and Technology in Wuhan, China.

Research Interests: Learning Causality with Data, Machine Learning and Social Media Mining.

When Ruocheng is not working on research, he may play basketball, cook, go hiking, watch soccer, NBA and Dota2 games and listen to various types of music.

Ruocheng Guo

Don't hasitate to contact me through:
rguo12 at asu dot edu

Data Mining and Machine Learning Lab
Arizona State University
699 Mill Ave BYENG
Tempe, AZ 85281
USA

News

[October 2018] The paper Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles got accepted in WSDM 2019 as a full research paper!
[September 2018] A Survey of Learning Causality with Data: Problems and Methods is available on [arxiv]!
[August 2018] Ruocheng received the SIGIR travel grant for CIKM 2018!
[July 2018] The paper Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects got accepted in CIKM 2018 as a short paper! Looking forward to meeting you in Turin!
[June 2018] Ruocheng received the Engineering Graduate Fellowship from CIDSE, ASU!
[April 2018] The paper INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process got accepted in IJCAI-ECAI 2018!

Publications

Preprint

Conference Papers

  • Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects
    Ruocheng Guo*, Vineeth Rakesh*, Raha Moraffah, Nitin Agarwal and Huan Liu (* Equal Contribution)
    CIKM 2018 (short paper, acceptance rate 23.4%)
    [arxiv] [pdf] [code]

  • INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process
    Ruocheng Guo, Jundong Li and Huan Liu
    IJCAI-ECAI 2018 (acceptance rate 20.5%)
    [pdf]

  • Strongly Hierarchical Factorization Machines and ANOVA Kernel Regression
    Ruocheng Guo, Hamidreza Alvari and Paulo Shakarian
    SDM 2018 (acceptance rate 23.2%)
    [arxiv] [appendix]
    A 20k sample from When Do You Retweet dataset [Download]

  • A Comparison of Methods for Cascade Prediction
    Ruocheng Guo and Paulo Shakarian
    ASONAM 2016
    [arxiv]

  • Towards Order-of-magnitude Cascade Prediction
    Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar and Paulo Shakarian
    ASONAM 2015
    [arxiv]

  • Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles
    Ghazaleh Beigi, Ruocheng Guo, Alex Nou, Yanchao Zhang and Huan Liu
    WSDM 2019
    [To appear]

  • Detecting Pathogenic Social Media Accounts without Content or Network Structure
    Elham Shaabani, Ruocheng Guo and Paulo Shakarian
    ICDIS 2018 (Best Poster)
    [pdf]

  • Temporal Analysis of Influence to Predict Users’ Adoption in Online Social Networks
    Ericsson Marin, Ruocheng Guo and Paulo Shakarian
    SBP 2017
    [arxiv]

Journal Papers

  • Toward Early and Order-of-magnitude Cascade Prediction in Social Networks
    Ruocheng Guo, Elham Shaabani, Abhinav Bhatnagar and Paulo Shakarian
    SNAM 2016
    [arxiv]

  • Understanding and Forecasting Lifecycle Events in Information Cascades
    Soumajyoti Sarkar, Ruocheng Guo and Paulo Shakarian
    SNAM 2017
    [arxiv]

Book

Workshop Papers

Website based on Plain Academic